Data in Brief最新文献_第6页

IndoHotelABSA: A large-scale aspect-based sentiment analysis dataset of Indonesian hotel reviews for hospitality CRM IndoHotelABSA：用于酒店业CRM的大型印尼酒店评论情感分析数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-03 DOI: 10.1016/j.dib.2026.113209

Xaverius Sika, Eko Sediyono, Irwan Sembiring, Teguh Wahyono, Eko Arip Winanto

{"title":"IndoHotelABSA: A large-scale aspect-based sentiment analysis dataset of Indonesian hotel reviews for hospitality CRM","authors":"Xaverius Sika, Eko Sediyono, Irwan Sembiring, Teguh Wahyono, Eko Arip Winanto","doi":"10.1016/j.dib.2026.113209","DOIUrl":"10.1016/j.dib.2026.113209","url":null,"abstract":"<div><div>IndoHotelABSA is a large-scale dataset for aspect-based sentiment analysis (ABSA) of Indonesian hotel reviews. It comprises 14,988 unique, deduplicated Indonesian-language reviews collected on 10 July 2026 through the official Google Places API from 3,075 establishments across 55 cities spanning all six major regions of Indonesia. A class-balanced sample of 3,000 reviews was annotated for seven CRM-meaningful aspect categories (Location, Cleanliness, Service/Staff, Room & Facilities, Price/Value, Food & Beverage, and Public Facilities), each with three-way polarity (positive, negative, neutral), using a two-tier protocol: all 3,000 reviews received large-language-model (LLM) draft labels, forming the <em>silver</em> tier, and a 500-review subset was checked and corrected independently by three human annotators and adjudicated by majority vote, forming the <em>gold</em> tier. The gold subset reaches almost-perfect agreement (Fleiss’ <span><math><mrow><mi>κ</mi><mo>=</mo><mn>0.894</mn></mrow></math></span>) and yields 1,506 gold aspect annotations. The release explicitly distinguishes the 2,480 unverified silver training records from the 500 human-verified gold records and provides fixed train/validation/test splits. The dataset fills the absence of a public, quality-controlled Indonesian hotel ABSA benchmark and can be reused for low-resource NLP, LLM-annotation research, and hospitality customer relationship management (CRM) analytics. All files are provided as UTF-8 JSON Lines with a datasheet and annotation guidelines.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113209"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148999683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AudioHate-DB: An audio dataset for English hate speech detection in Bengali accent AudioHate-DB：一个用于孟加拉口音英语仇恨言论检测的音频数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-11 DOI: 10.1016/j.dib.2026.113258

Arif Faisal, Syeda Sumaia Sultana, Suprove Chandra Sarkar, Shabnom Mustary

{"title":"AudioHate-DB: An audio dataset for English hate speech detection in Bengali accent","authors":"Arif Faisal, Syeda Sumaia Sultana, Suprove Chandra Sarkar, Shabnom Mustary","doi":"10.1016/j.dib.2026.113258","DOIUrl":"10.1016/j.dib.2026.113258","url":null,"abstract":"<div><div>Hate speech detection has gained significant attention in recent years due to the rapid increase in offensive and harmful content across social media and other digital platforms. Although there are many resources for written hate speech and for accented native English, there are few resources for offensive English speech in South Asian accents, which hinders the development of accent-aware hate speech detection and speech recognition systems. To address this need, the following paper introduces a speech dataset for hate speech detection in spoken English with a Bangladeshi accent, in which slurs, gendered epithets, and general profanity are mixed with otherwise neutral English speech, which is prevalent in Bangladesh and South Asia. This dataset contains 3018 audio samples with a controlled sentence inventory of 1006 sentences (505 hate-class, 501 non-hate-class). Every hateful class sentence has at least one word from a set of 23 hateful terms divided into six semantic categories: racial slurs, gendered/sexual slurs, ability derogatory terms, LGBTQ+ slurs, profanity, and compound/contextual words. Audio samples were collected on mobile telephones using a 44,100 Hz, 16-bit depth format and by multi-regional, multi-gender speakers in natural indoor and outdoor settings and were recorded for two balanced classes. Both raw and noise-cancelled processed versions are offered, where the class name is represented by the directory structure. Baseline experiments using Logistic Regression, Random Forest, Gradient Boosting, and LSTM demonstrate the dataset’s effectiveness, with LSTM achieving the highest accuracy of 83.94%. The dataset can support research on spoken hate speech detection, accent-aware speech recognition, and audio content moderation.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113258"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148999677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset of volatile profiles and sensory evaluation of commercial maize snacks from Colombia using headspace gas chromatography–mass spectrometry 用顶空气相色谱-质谱法分析哥伦比亚商品玉米零食的挥发性特征和感官评价数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-08 DOI: 10.1016/j.dib.2026.113232

Juan E. Mora-Zarate, Claudia L. Garzón-Castro, Annamaria Filomena-Ambrosio, Natalia Conde-Martínez

{"title":"Dataset of volatile profiles and sensory evaluation of commercial maize snacks from Colombia using headspace gas chromatography–mass spectrometry","authors":"Juan E. Mora-Zarate, Claudia L. Garzón-Castro, Annamaria Filomena-Ambrosio, Natalia Conde-Martínez","doi":"10.1016/j.dib.2026.113232","DOIUrl":"10.1016/j.dib.2026.113232","url":null,"abstract":"<div><div>This article presents a dataset integrating Headspace Gas Chromatography–Mass Spectrometry (HS-GC-MS) analyses and descriptive sensory evaluation data for three commercially available maize-based snack products from the Colombian market. The dataset was developed to support research in food science, sensory analysis, chemometrics, and predictive modeling of food perception. HS-GC-MS analyses were performed in triplicate for each product, generating nine chromatographic files in (.cdf) format and a processed dataset containing retention times, retention indices, peak areas, and tentative volatile compound identifications. In parallel, a semi-trained sensory panel composed of 32 participants evaluated 17 sensory descriptors associated with odor, taste, and texture using a structured intensity scale. To assess the statistical value of chromatographic data, a Partial Least Squares Discriminant Analysis (PLS-DA) model was developed using volatile compound profiles. The model showed a clear discrimination among the three products, with the first two components explaining 97.3 % of the total variance. Variable Importance in Projection (VIP) analysis identified terpene-related compounds, including β-pinene, limonene, γ-terpinene, α-pinene, and p-cymene, as the main contributors to sample differentiation. Cross-validation demonstrated excellent model performance with R² = 0.99 and Q² = 0.98. The dataset provides openly accessible chromatographic and sensory information that may support comparative studies, food quality assessment, sensory prediction models, and the development of novel maize-based food products.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113232"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149006291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CompPhish: A comprehensive dataset for diversified phishing detection CompPhish：一个全面的数据集，用于多种网络钓鱼检测

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-03 DOI: 10.1016/j.dib.2026.113219

Richa Goenka, Meenu Chawla, Namita Tiwari

{"title":"CompPhish: A comprehensive dataset for diversified phishing detection","authors":"Richa Goenka, Meenu Chawla, Namita Tiwari","doi":"10.1016/j.dib.2026.113219","DOIUrl":"10.1016/j.dib.2026.113219","url":null,"abstract":"<div><div>Most of the cyber attacks are initiated through phishing URLs, which are shared with the victims through multiple media. In spite of the research community proposing varied solutions, the volume and nature of such attacks have evolved unpredictably. To develop effective solutions, researchers require comprehensive datasets that encompass a wide range of attack types rather than focusing on a narrow subset. We present CompPhish, a processed dataset, comprising of 15,358 URLs paired with their respective HTML sources. 7204 URLs are phishing, and 8154 are legitimate. A set of 70 features, specifically curated to capture the properties exhibited by phishing URLs, is extracted. These features represent a diverse range of phishing attacks, including generic URL-based phishing attacks, phishing through brand-jacking, phishing sites hosted on compromised domains, and auto-downloadable malicious files embedded in webpages. Phishing URLs are gathered from PhishTank and OpenPhish, while legitimate URLs are compiled from multiple independent sources, like DataforSEO and GitHub.</div><div>By publishing the raw URLs and HTML codes along with the feature vectors, CompPhish attempts to aid the researchers in devising generalized, robust, and reliable machine learning based solutions for real-world phishing attempts.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113219"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148949318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Preliminary Study of the Metagenomic Dataset of Bacterial Endophyte Communities in Cultivated Pisang Awak Banana 栽培Pisang Awak香蕉细菌内生菌群落宏基因组数据集的初步研究

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-08-25 DOI: 10.1016/j.dib.2026.113186

Le Nguyen Tieu Ngoc, Thi Huyen Nguyen, Dinh Minh Tran

{"title":"Preliminary Study of the Metagenomic Dataset of Bacterial Endophyte Communities in Cultivated Pisang Awak Banana","authors":"Le Nguyen Tieu Ngoc, Thi Huyen Nguyen, Dinh Minh Tran","doi":"10.1016/j.dib.2026.113186","DOIUrl":"10.1016/j.dib.2026.113186","url":null,"abstract":"<div><div>Pisang Awak is an important banana cultivar widely grown in Dak Lak Province, Vietnam. Despite its agricultural significance, no information is available regarding the composition of its endophytic bacterial community. This study was conducted to establish a 16S rRNA gene metagenomic dataset of endophytic bacteria present within the internal root tissues of Pisang Awak banana cultivated in Dak Lak Province. The analysis identified 15 bacterial phyla, 22 classes, 52 orders, 68 families (including two uncultured groups), and 101 genera (including 11 uncultured groups). Among these, the phylum <em>Actinobacteriota</em> was the most dominant, accounting for 35.73% of the bacterial community, while biosynthesis-related functions represented the most abundant functional category (72.04%). At the genus level, <em>Bacillus</em> (35.58%) and <em>Streptomyces</em> (25.56%) were predominant, whereas <em>Bacillus megaterium</em> (27.39%) was the most abundant identified species. These findings provide valuable insights into the endophytic bacterial community inhabiting the internal root tissues of Pisang Awak banana grown in Dak Lak. The dataset may support future experiments aimed at developing biofertilizers for Pisang Awak banana production using indigenous endophytic bacteria and can serve as a valuable resource for further exploration of uncultured bacterial taxa. This is the first report describing the endophytic bacterial dataset of the internal root tissues of Pisang Awak banana cultivated in Dak Lak, Vietnam.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"68 ","pages":"Article 113186"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148952304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-throughput sequencing dataset of raw and treated wastewater from Jeddah, Saudi Arabia 来自沙特阿拉伯吉达的未经处理的废水的高通量测序数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-08-25 DOI: 10.1016/j.dib.2026.113174

Manish P. Victor, Nawaf Al Shehri, Didrik H. Grevskott, Walied M. Alarif, Aasim M. Ali, Nachiket P. Marathe

引用次数: 0

Workpiece temperature field and process force data for turning steel and aluminum alloy under varying machining parameters 不同加工参数下车削钢和铝合金的工件温度场和加工力数据

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-04 DOI: 10.1016/j.dib.2026.113240

Lars Langenhorst, Jens Sölter

{"title":"Workpiece temperature field and process force data for turning steel and aluminum alloy under varying machining parameters","authors":"Lars Langenhorst, Jens Sölter","doi":"10.1016/j.dib.2026.113240","DOIUrl":"10.1016/j.dib.2026.113240","url":null,"abstract":"<div><div>Cylindrical workpieces made of AISI 4140 steel and A97075 aluminum alloy were machined in an external longitudinal turning process using uncoated cemented carbide cutting tools without metal working fluid. During machining, the process forces were measured by means of piezoelectric sensors within a dynamometer. In addition, temperature on the workpiece surface was measured using infrared thermography. The dataset provides the process forces as raw data over the process time, along with the calculated mean values and standard deviations for each test point within the investigated design of experiments, in which the depth of cut, spindle rotation speed, and feed rate are varied. The process temperatures measured along a focused line in feed direction are also provided as raw data and mean values over time and corresponding uncertainty for all experiments. In metal cutting, an understanding of the process forces, which act as external loads on the workpiece, and the workpiece temperature, as an internal material load, is closely linked to the subsequent functional performance of the final component. Reuse potential thus lies primarily in explaining modifications of material properties in the surface layer of the workpiece and its geometric deviations due to cutting and also in using the data for validation of modelling approaches. For analyzing tool wear, process forces and temperatures are also important factors. This dataset enables such analyses without having to repeat the time-consuming calibration of temperature measurement systems and preparation of machining tests.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113240"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148940406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

16S rRNA gene amplicon data from four composite gut-region samples of Microcerotermes diversus workers 四种不同工蚁肠道复合样本的16S rRNA基因扩增子数据

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-10-01 DOI: 10.1016/j.dib.2026.113302

Seyed Qasem Mousavi, Azam Amiri, Ali R. Bandani

{"title":"16S rRNA gene amplicon data from four composite gut-region samples of Microcerotermes diversus workers","authors":"Seyed Qasem Mousavi, Azam Amiri, Ali R. Bandani","doi":"10.1016/j.dib.2026.113302","DOIUrl":"10.1016/j.dib.2026.113302","url":null,"abstract":"<div><div>This data article describes bacterial V3-V4 16S rRNA gene amplicon data from four anatomically defined composite gut preparations of <em>Microcerotermes diversus</em> workers. Termites were collected from infested <em>Morus nigra</em> branches in Shush, Khuzestan Province, southwestern Iran. Guts from 400 workers were dissected into four anatomical categories, and corresponding tissues were pooled to generate one composite DNA sample and one sequencing library per category. The amplicons were sequenced on an Illumina MiSeq platform using a 2 × 300-bp paired-end configuration. Public resources comprise quality-filtered paired-end FASTQ files in the NCBI Sequence Read Archive under BioProject PRJNA1328141, 82 representative partial 16S rRNA gene sequences in GenBank under accessions PX349529-PX349610, and processed OTU, taxonomic, diversity, and rarefaction records in Figshare, together with four pH records reported in this article. Sample identifiers T1-T4 link the anatomical definitions, sequence runs, processed outputs, tables, and figures. The archived reads and processed files can be used for sample-level reanalysis, taxonomic reclassification, workflow benchmarking, and harmonized comparison with independently generated termite microbiome data.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113302"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149143445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset of UAV-acquired thermal and visible images for solar photovoltaic hotspot detection using MLX90640BAB and raspberry Pi 5 基于MLX90640BAB和树莓派5的太阳能光伏热点探测无人机热可见光图像数据集

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-09-25 DOI: 10.1016/j.dib.2026.113288

Farhan Ferdous, Bishwajit Banik Pathik, Mushfiqur Rahman, Ahnaf Tahamid, Fauzia Fariha Trona

{"title":"Dataset of UAV-acquired thermal and visible images for solar photovoltaic hotspot detection using MLX90640BAB and raspberry Pi 5","authors":"Farhan Ferdous, Bishwajit Banik Pathik, Mushfiqur Rahman, Ahnaf Tahamid, Fauzia Fariha Trona","doi":"10.1016/j.dib.2026.113288","DOIUrl":"10.1016/j.dib.2026.113288","url":null,"abstract":"<div><div>Hotspots are among the most common and damaging thermal anomalies in solar photovoltaic (PV) modules, indicating localized cell defects, shading or soiling that reduce energy yield and can shorten module lifespan [1,2]. However, publicly available thermal image datasets for PV hotspot detection remain scarce, particularly datasets acquired with low-cost thermal sensors in South Asian operating conditions. This article presents a dataset of UAV acquired thermal fusion and visible images of operating rooftop PV modules collected in Dhaka, Bangladesh. Fifty raw samples were captured across two sites: 25 at Mirpur on 06 June 2026 and 25 at Mohammadpur on 22 June 2026. Images were acquired using a custom built quadcopter carrying a Raspberry Pi 5 interfaced with an MLX90640BAB far infrared thermal array sensor which produced color thermal fusion images with on screen maximum temperature readouts and a Raspberry Pi Camera NoIR V2 for visible imagery. The 50 raw samples were expanded to a 5000 image dataset through pre-processing, data augmentation and annotated with bounding boxes for a single Hotspot class (4,626 labeled instances in the training split). A YOLO26s detector trained on the dataset for 95 epochs on an NVIDIA A100 GPU achieved a precision of 0.947, recall of 0.889, [email protected] of 0.936 and [email protected]:0.95 of 0.878 on the validation split which confirms that the dataset supports supervised hotspot detection research. The dataset is suitable for benchmarking object detection algorithms by developing low cost aerial PV inspection pipelines and training edge deployable models for automated PV monitoring.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113288"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149143450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Surveillance camera image dataset for visual classification in criminal investigation research (CCTV cameras) 用于刑侦研究视觉分类的监控摄像机图像数据集（CCTV摄像机）

IF 1.9

Data in Brief Pub Date : 2026-08-01 Epub Date: 2026-10-07 DOI: 10.1016/j.dib.2026.113322

Dimitar Rangelov, Nikolay Rangelov, Radoslav Miltchev, Evgeni Genchev

{"title":"Surveillance camera image dataset for visual classification in criminal investigation research (CCTV cameras)","authors":"Dimitar Rangelov, Nikolay Rangelov, Radoslav Miltchev, Evgeni Genchev","doi":"10.1016/j.dib.2026.113322","DOIUrl":"10.1016/j.dib.2026.113322","url":null,"abstract":"<div><div>This data article describes a curated collection of 1421 images of civilian surveillance and security cameras, assembled to support computer vision research on the visual recognition of camera systems in real-world environments. The images were gathered from freely reusable web sources, open image repositories, and manufacturer product pages, and every image was manually reviewed so that each retained file clearly depicts at least one surveillance camera. The collection covers the most common camera form factors, including dome, pan-tilt-zoom (PTZ), bullet, fixed box, multi-sensor, and consumer IP or doorbell cameras, photographed in outdoor street installations, indoor security setups, pole-mounted and wall-mounted configurations, as well as manufacturer product imagery against plain backgrounds. All files follow a sequential naming convention (camera_<ID>) and are provided in a single directory in JPEG format, in RGB colour space, standardised to a uniform resolution of 640 × 640 pixels. A lightweight annotation file (labels.csv) accompanies the images, recording for each file whether it depicts a camera installed in a real environment (718 in-situ photographs) or a manufacturer-style product image (703 images), together with a per-image camera_type label giving the form factor of the device shown. A documented Python loading script and SHA-256 checksums are distributed with the data. The dataset is publicly available on Zenodo under a CC BY 4.0 licence. It can be reused to train and benchmark image classification and object detection models for automated camera canvassing at crime scenes, and to support research in digital forensics, privacy auditing, urban surveillance mapping, and smart-city applications.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"69 ","pages":"Article 113322"},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149201648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0