2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)最新文献_第2页

Reducing Modern Slavery Using AI and Blockchain 利用人工智能和区块链减少现代奴隶制

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311031

Pratap Tambe, Dr Prerna Tambay

引用次数: 4

Probabilistic Interpretation from Behavior and Entropy of Nonlinear Cognitive Radio Networks with Quantum Mechanics Theory 基于量子力学理论的非线性认知无线网络行为和熵的概率解释

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311019

H. Nieto-Chaupis

引用次数: 0

Preliminary Results of a Global Database on Soft Law Mechanisms for the Governance of Artificial Intelligence 人工智能治理软法律机制全球数据库的初步结果

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311078

C. I. Gutierrez, G. Marchant, Alec Carden, Kaylee Hoffner, Alexander Kearl

{"title":"Preliminary Results of a Global Database on Soft Law Mechanisms for the Governance of Artificial Intelligence","authors":"C. I. Gutierrez, G. Marchant, Alec Carden, Kaylee Hoffner, Alexander Kearl","doi":"10.1109/AI4G50087.2020.9311078","DOIUrl":"https://doi.org/10.1109/AI4G50087.2020.9311078","url":null,"abstract":"Soft law mechanisms create substantive expectations that are not directly enforceable by government. All kinds of organizations apply soft law to regulate the development or use of methods and applications of artificial intelligence (AI), yet limited scholarship is devoted to studying the prevalence of these tools. This article describes the methodology and preliminary results of a project that compiled a global database of AI soft law mechanisms. It provides information on the type of organizations that create them, differences in how they are enforced, their origin and jurisdiction, influence, and the themes of their text. As both developers and users of these mechanisms, stakeholders (private sector, governments, and civil society) need information about their option space on how to govern AI. The objective of this work is to make available an analysis and library of information that facilitates the development of effective soft law mechanisms. In addition, it offers readers unique insights into the role of these mechanisms in managing AI's outcomes.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127086214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Building Ethical AI from News Articles 从新闻文章中构建道德AI

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311054

Wonchul Kim, Keeheon Lee

引用次数: 2

Automatic identification of skin lesions using deep learning techniques 使用深度学习技术自动识别皮肤病变

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311068

Madhurshalini M, Chitra Nair, Nidhi Goel

{"title":"Automatic identification of skin lesions using deep learning techniques","authors":"Madhurshalini M, Chitra Nair, Nidhi Goel","doi":"10.1109/AI4G50087.2020.9311068","DOIUrl":"https://doi.org/10.1109/AI4G50087.2020.9311068","url":null,"abstract":"Cutaneous diseases or Skin Diseases are one of the most common diseases affecting nearly 2 out of every 3 people. However, WHO and the world bank records show that 50% of the world lacks access to essential healthcare. This is more prevalent for skincare. This lack of accessible skincare and a highly prevalent misdiagnosis of skin diseases demands alternate approaches to achieve universal skincare coverage. Technology holds the potential to bridge this gap between patient requirements and quality healthcare. Historically the research on utilising technology to provide dermatology care has been limited to teledermatoscopy and decision mechanisms on images. This research proposes a method considering disease images and the symptoms experienced in the diagnostics. Different deep convolutional neural network architectures are evaluated to choose the best one for an image-based classifier, and a feed-forward neural network for a symptom-based classifier, the results of each combined to yield the outcome. The ensemble method classifies the disease from symptoms and image with an accuracy of 87.71%. This approach can potentially be used to provide quality accessible skincare over the world through web and mobile applications bringing us one step closer in achieving the United Nations good-health and well-being sustainability goals.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124161441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

EdgeAI: Diabetic Retinopathy Detection in Intel Architecture 基于Intel架构的糖尿病视网膜病变检测

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311036

Gina Mathew, S. Sindhu Ramachandran, Suchithra V.S.

{"title":"EdgeAI: Diabetic Retinopathy Detection in Intel Architecture","authors":"Gina Mathew, S. Sindhu Ramachandran, Suchithra V.S.","doi":"10.1109/AI4G50087.2020.9311036","DOIUrl":"https://doi.org/10.1109/AI4G50087.2020.9311036","url":null,"abstract":"Diabetic retinopathy is a leading cause of blindness among working-age adults. Millions of people suffer from Diabetic Retinopathy in India. More dreaded situation is faced by the population in rural India where access to quality healthcare is limited. AI comes to the rescue in those situations where initial diagnosis can be performed without much manual intervention. Early detection of this condition is critical for good prognosis. In this paper we propose a solution using UP2 board (Edge device based on x86 architecture) where AI diagnosis can be performed on the local premise itself. We used PyTorch framework for training the model using EfficientNet-B4 network architecture. Trained model was optimized using Intel Distribution of Open-VINO, and hence there is no much compromise in execution time. Inference time for execution of single image in UP2 board is 0.2 sec. Our model achieved test metric performance comparable to baseline literature results, with sensitivity of 91.5% and specificity of 97.86%. For proof of concept we used open dataset from Kaggle 2019 competition hosted by Aravind Hospital, India.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Combating Deepfakes: Multi-LSTM and Blockchain as Proof of Authenticity for Digital Media 打击深度造假:多lstm和区块链作为数字媒体真实性的证明

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311067

Christopher Chun Ki Chan, Vimal Kumar, Steven Delaney, Munkhjargal Gochoo

{"title":"Combating Deepfakes: Multi-LSTM and Blockchain as Proof of Authenticity for Digital Media","authors":"Christopher Chun Ki Chan, Vimal Kumar, Steven Delaney, Munkhjargal Gochoo","doi":"10.1109/AI4G50087.2020.9311067","DOIUrl":"https://doi.org/10.1109/AI4G50087.2020.9311067","url":null,"abstract":"Malicious use of deep learning algorithms has allowed the proliferation of high realism fake digital content such as text, images, and videos, to exist on the internet as readily available and accessible consumable content. False information provided through algorithmically modified footage, images, audios, and videos (known as deepfakes), coupled with the virality of social networks, may cause major social unrest. The emergence of misinformation from fabricated digital content suggests the necessity for anti-disinformation methods such as deepfake detection algorithms or immutable metadata in order to verify the validity of digital content. Permissioned blockchain, notably Hyperledger Fabric 2.0, coupled with LSTMs for audio/video/descriptive captioning is a step towards providing a feasible tool for combating deepfake media. Original content would require the original artist attestation of untampered data. The smart contract combines a varied multiple LSTM networks into a process that allows for the tracing and tracking of a digital content's historical provenance. The result is a theoretical framework that enables proof of authenticity (PoA) for digital media using a decentralized blockchain using multiple LSTMs as a deep encoder for creating unique discriminative features; which is then compressed and hashed into a transaction. Our work assumes we trust the video at the point of reception. Our contribution is a decentralized blockchain framework of deep discriminative digital media to combat deepfakes.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"109 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116170512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Optimizing Networked Rural Electrification Design using Adaptive Multiplier-Accelerated A* Algorithm 基于自适应乘数加速A*算法的网络化农村电气化优化设计

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311085

Jerry Chun-Fung Li, D. Zimmerle, P. Young

引用次数: 2

IMPACT: a strategic partnership for sustainable development in marine systems and robotics 影响:为海洋系统和机器人的可持续发展建立战略伙伴关系

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311023

F. Maurelli, S. Krupinski, A. Pascoal, N. Mišković, Kostas Kyriakopolous, P. Ridao, M. Kruusmaa, R. Bachmayer

引用次数: 4

AI-Vision Towards an Improved Social Inclusion 面向改善社会包容的人工智能愿景

2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G) Pub Date : 2020-09-21 DOI: 10.1109/AI4G50087.2020.9311049

Rasem Alashkar, Mohamed ElSabbahy, Ahmad Sabha, Momen Abdelghany, B. Tlili, Jinane Mounsef

{"title":"AI-Vision Towards an Improved Social Inclusion","authors":"Rasem Alashkar, Mohamed ElSabbahy, Ahmad Sabha, Momen Abdelghany, B. Tlili, Jinane Mounsef","doi":"10.1109/AI4G50087.2020.9311049","DOIUrl":"https://doi.org/10.1109/AI4G50087.2020.9311049","url":null,"abstract":"The promise of Artificial Intelligence (AI)-based technologies is immense, and benefits range from efficiency profits to unprecedented improvements of quality of life in a social exclusive world, where discrimination and marginalization pose significant difficulties for building inclusive cities and providing equal access to opportunities for disabled persons. The challenges faced by visually impaired individuals in today's world are too many to count. While many tools have been introduced to help address these problems, these tools remain very costly to afford. The proposed smart glasses AI-Vision, which aim to provide the needed support in daily routine tasks utilizes machine learning algorithms in two applications of great interest. A facial expression/age/gender recognition for meetings, and a color recognition for outfit sorting are integrated in the device's framework. The generated feedback sound can be heard by the user through the bone conduction technology while avoiding disturbance of surrounding noise. The proposed AI-Vision reduces substantially the cost of a similar product while keeping an efficient recognition accuracy.","PeriodicalId":286271,"journal":{"name":"2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132210855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2