Browsing by Subject "Deep learning"
Now showing items 21-27 of 27
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More learning with less labeling for face recognition
(Elsevier, 2023-05)In this paper, we propose an improved face recognition framework where the training is started with a small set of human annotated face images and then new images are incorporated into the training set with minimum human ... -
Neural network estimatorsfor optimal tour lengths of TSP instances with arbitrary node distributions
To achieve operational efficiency in logistics, we need to solve complex routing problems. Due to their complexity, these problems are often solved sequentially, i.e., using cluster-first route-second (CFRS) type frameworks. ... -
NFT primary sale price and secondary sale prediction via deep learning
(Association for Computing Machinery, Inc, 2023-11-27)Non Fungible Tokens (NFTs) are blockchain-based unique digital assets defining ownership deeds. They can characterize various different objects such as collectible, art, and in-game items. In general, NFTs are encoded by ... -
Not all mistakes are equal
(The ACM Digital Library, 2020)In many tasks, classifiers play a fundamental role in the way an agent behaves. Most rational agents collect sensor data from the environment, classify it, and act based on that classification. Recently, deep neural networks ... -
Offloading deep learning powered vision tasks from UAV to 5G edge server with denoising
(IEEE, 2023-06)Offloading computationally heavy tasks from an unmanned aerial vehicle (UAV) to a remote server helps improve battery life and can help reduce resource requirements. Deep learning based state-of-the-art computer vision ... -
Tamper-proof evidence via blockchain for autonomous vehicle accident monitoring
(IEEE, 2022)In case of an accident between two autonomous vehicles equipped with emerging technologies, how do we apportion liability among the various players? A special liability regime has not even yet been established for damages ... -
YOLODrone+: improved YOLO architecture for object detection in UAV images
(IEEE, 2022)The performance of object detection algorithms running on images taken from Unmanned Aerial Vehicles (UAVs) remains limited when compared to the object detection algorithms running on ground taken images. Due to its various ...
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