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pro vyhledávání: '"A Fateh"'
FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
Early detection of lung cancer is crucial as it increases the chances of successful treatment. Automatic lung image segmentation assists doctors in identifying diseases such as lung cancer, COVID-19, and respiratory disorders. However, lung segmentat
Externí odkaz:
http://arxiv.org/abs/2410.15812
This paper introduces TemporalVLM, a video large language model capable of effective temporal reasoning and fine-grained understanding in long videos. At the core, our approach includes a visual encoder for mapping a long-term input video into featur
Externí odkaz:
http://arxiv.org/abs/2412.02930
This research presents and compares multiple approaches to automate the generation of literature reviews using several Natural Language Processing (NLP) techniques and retrieval-augmented generation (RAG) with a Large Language Model (LLM). The ever-i
Externí odkaz:
http://arxiv.org/abs/2411.18583
Autor:
Aliyev, Fateh, Gladkov, Nikita
We establish a lower bound on the forcing numbers of domino tilings computable in polynomial time based on height functions. This lower bound is sharp for a 2n by 2n square as well as other cases.
Comment: 10 pages, 4 figures
Comment: 10 pages, 4 figures
Externí odkaz:
http://arxiv.org/abs/2410.23621
In recent years, significant progress has been made in the field of state transfer in spin chains, with the aim of achieving perfect state transfer for quantum information processing applications. Previous research has mainly focused on manipulating
Externí odkaz:
http://arxiv.org/abs/2410.14053
This paper introduces BAKUP, a smart contract insurance design for decentralized finance users to mitigate risks arising from platform vulnerabilities. While providing automated claim payout, BAKUP utilizes a modular structure to harmonize three key
Externí odkaz:
http://arxiv.org/abs/2410.09341
Pneumonia, a severe respiratory disease, poses significant diagnostic challenges, especially in underdeveloped regions. Traditional diagnostic methods, such as chest X-rays, suffer from variability in interpretation among radiologists, necessitating
Externí odkaz:
http://arxiv.org/abs/2408.04290
Few-shot Semantic Segmentation addresses the challenge of segmenting objects in query images with only a handful of annotated examples. However, many previous state-of-the-art methods either have to discard intricate local semantic features or suffer
Externí odkaz:
http://arxiv.org/abs/2409.11316
In the context of few-shot classification, the goal is to train a classifier using a limited number of samples while maintaining satisfactory performance. However, traditional metric-based methods exhibit certain limitations in achieving this objecti
Externí odkaz:
http://arxiv.org/abs/2409.07989
Autor:
Fokoue, Achille, Jayaraman, Srideepika, Khabiri, Elham, Kephart, Jeffrey O., Li, Yingjie, Shah, Dhruv, Drissi, Youssef, Heath III, Fenno F., Bhamidipaty, Anu, Tipu, Fateh A., Baseman, Robert J.
In many industrial settings, users wish to ask questions whose answers may be found in structured data sources such as a spreadsheets, databases, APIs, or combinations thereof. Often, the user doesn't know how to identify or access the right data sou
Externí odkaz:
http://arxiv.org/abs/2409.05735