This work presents an innovative approach to image-to-image translation, focusing on converting colour pencil images, grayscale pencil images, and grayscale images into RGB images using the Pix2Pix GAN. Building upon ...
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Navigation for mobile robots is critical for the deployment and use of robots. Without the ability to interact with the world a robot cannot bring to bear its utility. This work further explores the properties of a mo...
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Autonomous vehicles are poised to revolutionize the transportation industry by offering safer and more efficient navigation in dynamic environments. A critical challenge is managing interactions with other vehicles, p...
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This paper proposes a new three-phase multi-mode AC/DC LLC resonant converter with an output-controlled active rectifier for electric vehicle (EV) fast DC charging applications. In the proposed approach, two low-frequ...
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This study explores the use of Natural Language Processing (NLP) approach to predict Myers-Briggs Type Indicator (MBTI) personality types from Twitter texts. Initially, we approached the problem as a 16-class classifi...
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Remote sensing data is used in various fields, such as environmental monitoring, urban planning, agriculture, and disaster management. Advances in satellite technology permit the creation of high-quality data, includi...
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In this paper we introduce a novel dataset of high altitude aerial images with manual annotations for impervious surfaces from a predominantly urban area. The dataset also contains a small amount of hand annotations f...
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Colorectal polyps are benign lesions that develop in the colon and can progress to cancer if left untreated. Clinical observations from medical images are often preferred over computational results due to the lac...
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Colorectal polyps are benign lesions that develop in the colon and can progress to cancer if left untreated. Clinical observations from medical images are often preferred over computational results due to the lack of trust in the machine learning models, thereby posing serious challenge for the explainability of the results. In order to computationally diagnose colorectal polyps from cancerous images and explain the results, we propose a Layer-wise eXplainable ResUNet++ (LeXNet++) framework for segmentation of the cancerous images, followed by layer-wise explanation of the results. We utilize a publicly accessible dataset that contains of 612 raw images with a resolution of 256×256×3 and an additional 612 clinically annotated and labeled images with a resolution of 256×256×1, which includes the infected region. The LeXNet++ framework comprises of three components—encoder, decoder and the bridge. The encoder and the decoder components each comprise of four layers. Each of the four layers in the encoder and the decoder comprises of 14 and 11 internal sub-layers, respectively. Among the sub-layers of the encoder and the decoder, there are three 3×3 convolutional layers with an additional 3×3 convolution-transpose layer in the decoder. The output of each of the sub-layers has been explained through heatmap generation after each iteration which have been further explained. The encoder and the decoder are connected by the bridge which comprises of three sub-layers. The results obtained from these three sub-layers have also been explained to inculcate trust in the findings. In this study, we have used three models to segment the images, namely UNet, ResUNet, and proposed LeXNet++. LeXNet++ exhibited the best result among the three models in terms of performance;hence, only LeXNet++ was explained layer-wise. Apart from explanation of the results fetched in this study, the performance of the proposed explainable model has been observed to be 2% greater than the existing poly
American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algori...
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In the context of Industry 5.0 and human-robot interaction, ensuring the safety of operators by avoiding human errors is crucial. Monitoring vigilance decrement is an essential aspect of this effort, aimed at mitigati...
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