Essays about: "feature ablation"
Showing result 1 - 5 of 6 essays containing the words feature ablation.
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1. Hybrid Deep Learning approach for Lane Detection : Combining convolutional and transformer networks with a post-processing temporal information mechanism, for efficient road lane detection on a road image scene
University essay from Jönköping University/Jönköping AI Lab (JAIL)Abstract : Lane detection is a crucial task in the field of autonomous driving and advanced driver assistance systems. In recent years, convolutional neural networks (CNNs) have been the primary approach for solving this problem. READ MORE
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2. Information Extraction from Invoices using Graph Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Information Extraction is a sub-field of Natural Language Processing that aims to extract structured data from unstructured sources. With the progress in digitization, extracting key information like account number, gross amount, etc. from business invoices becomes an interesting problem in both industry and academy. READ MORE
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3. Investigation of High-Temperature Sensors for Tube Monitoring Applications
University essay from Uppsala universitet/SolcellsteknikAbstract : This report covers the investigation of the next generation of sensors to be used in the sensor based tube system known as SentusysTM. One essential feature of the next generation of sensors is high-temperature endurance. READ MORE
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4. Pedestrian Multiple Object Tracking Using Deep Learning
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : In this thesis, the aim is to examine the viability of Deep Neural Network (DNN) based Multi-Object Tracking approaches for tracking pedestrians. The tracking results are used for Autonomous Driver Assistance System (ADAS). The process of tracking multiple agents across video is termed as Multiple Object Tracking (MOT). READ MORE
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5. Designing a Performant Ablation Study Framework for PyTorch
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : PyTorch is becoming a really important library for any deep learning practitioner, as it provides many low-level functionalities that allow a fine-grained control of neural networks from training to inference, and for this reason it is also heavily used in deep learning research, where ablation studies are often conducted to validate neural architectures that researchers come up with. To the best of our knowledge, Maggy is the first open-source framework for asynchronous parallel ablation studies and hyperparameter optimization for TensorFlow, and in this work we added important functionalities such as the possibility to execute ablation studies on PyTorch models as well as the generalization of feature ablation on any data type. READ MORE