Zobrazeno 1 - 10
of 2 375
pro vyhledávání: '"Akbaş P"'
Autor:
Demir, Edanur, Akbas, Emre
This paper is aimed at developing a method that reduces the computational cost of convolutional neural networks (CNN) during inference. Conventionally, the input data pass through a fixed neural network architecture. However, easy examples can be cla
Externí odkaz:
http://arxiv.org/abs/2409.05336
Exoskeletons can boost human strength and provide assistance to individuals with physical disabilities. However, ensuring safety and optimal performance in their design poses substantial challenges. This study presents the design process for an under
Externí odkaz:
http://arxiv.org/abs/2408.07384
This paper introduces a multi-level, multi-label text classification dataset comprising over 3000 documents. The dataset features literary and critical texts from 19th-century Ottoman Turkish and Russian. It is the first study to apply large language
Externí odkaz:
http://arxiv.org/abs/2407.15136
Ranking-based loss functions, such as Average Precision Loss and Rank&Sort Loss, outperform widely used score-based losses in object detection. These loss functions better align with the evaluation criteria, have fewer hyperparameters, and offer robu
Externí odkaz:
http://arxiv.org/abs/2407.14204
Autor:
Hossain, Tanvir, Saifuddin, Khaled Mohammed, Islam, Muhammad Ifte Khairul, Tanvir, Farhan, Akbas, Esra
Graph Neural Network (GNN) achieves great success for node-level and graph-level tasks via encoding meaningful topological structures of networks in various domains, ranging from social to biological networks. However, repeated aggregation operations
Externí odkaz:
http://arxiv.org/abs/2407.11928
Recent advancements in quality control across various industries have increasingly utilized the integration of video cameras and image processing for effective defect detection. A critical barrier to progress is the scarcity of comprehensive datasets
Externí odkaz:
http://arxiv.org/abs/2406.07694
Autor:
Thapaliya, Bishal, Miller, Robyn, Chen, Jiayu, Wang, Yu-Ping, Akbas, Esra, Sapkota, Ram, Ray, Bhaskar, Suresh, Pranav, Ghimire, Santosh, Calhoun, Vince, Liu, Jingyu
Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix a
Externí odkaz:
http://arxiv.org/abs/2405.15805
Predicting events such as political protests, flu epidemics, and criminal activities is crucial to proactively taking necessary measures and implementing required responses to address emerging challenges. Capturing contextual information from textual
Externí odkaz:
http://arxiv.org/abs/2404.15612
Autor:
Ozer, Murat, Akbas, Halil, Onat, Ismail, Bastug, Mehmet, Akgul, Arif, ElSayed, Nelly, ElSayed, Zag, Koseli, Multu, Ekici, Niyazi
This study examines racial disparities in violent arrest outcomes, challenging conventional methods through a nuanced analysis of Cincinnati Police Department data. Acknowledging the intricate nature of racial disparity, the study categorizes explana
Externí odkaz:
http://arxiv.org/abs/2406.11867
This paper presents Key2Mesh, a model that takes a set of 2D human pose keypoints as input and estimates the corresponding body mesh. Since this process does not involve any visual (i.e. RGB image) data, the model can be trained on large-scale motion
Externí odkaz:
http://arxiv.org/abs/2404.07094