14 papers · ranked by Valyu relevance
Lidia Cleetus, A Raji Sukumar, N Hemalatha
In this paper, a detection tool has been built for the detection and identification of the diseases and pests found in the crops at its earliest stage. For this, various deep learning architectures were experimented to see which one of those would help in building a more accurate and an efficient detection model. The…
Reagan E. Mandiya, Hervé M. Kongo, Selain K. Kasereka, Kyamakya Kyandoghere + 4 more
Rapid and precise identification of Coronavirus Disease 2019 (COVID-19) is pivotal for effective patient care, comprehending the pandemic’s trajectory, and enhancing long-term patient survival rates. Despite numerous recent endeavors in medical imaging, many convolutional neural network-based models grapple with the…
Hadar Shavit, Filip Jatelnicki, Pol Mor-Puigventós, Wojtek Kowalczyk
In this paper, we present a modified Xception architecture, the NEXcepTion network. Our network has significantly better performance than the original Xception, achieving top-1 accuracy of 81.5% on the ImageNet validation dataset (an improvement of 2.5%) as well as a 28% higher throughput. Another variant of our model…
Md Humaion Kabir Mehedi, Kh. Fardin Zubair Nafis, Krity Haque Charu, Jia Uddin + 3 more
'Jia Uddin' 'Md Golam Rabiul Alam' 'M.F. Mridha' 'Asadullah Shaikh'] Arsenic contamination of drinking water is a significant health risk. Countries such as Bangladesh’s rural areas and regions are in the red alert zone because groundwater is the only primary source of drinking. Early detection of arsenic disease is…
WenKai Pan, Dong Zhu, Jutao Wang, Haiyan Zhu
This research paper presents a comprehensive investigation into the utilization of color image processing technologies and deep learning algorithms in the development of a robot vision system specifically designed for 8-ball billiards. The sport of billiards, with its various games and ball arrangements, presents…
Abid Mehmood, Yonis Gulzar, Qazi Mudassar Ilyas, Abdoh Jabbari + 3 more
'Muneer Ahmad' 'Sajid Iqbal' 'Ángele Juarranz'] Simple Summary Skin cancer is a major concern worldwide, and accurately identifying it is crucial for effective treatment. we propose a modified deep learning model called SBXception, based on the Xception network, to improve skin cancer classification. Using the HAM10000…
Kenan Morani, Esra Kaya Ayana, Devrim Ünay
The significance of efficient and accurate diagnosis amidst the unique challenges posed by the COVID-19 pandemic underscores the urgency for innovative approaches. In response to these challenges, we propose a transfer learning-based approach using a recently annotated Computed Tomography (CT) image database. While…
Daniel M. Tompkins, Kshitiz Kumar, Jian Wu
An Xception model reaches state-of-the-art (SOTA) accuracy on the ESC-50 dataset for audio event detection through knowledge transfer from ImageNet weights, pretraining on AudioSet, and an on-the-fly data augmentation pipeline. This paper presents an ablation study that analyzes which components contribute to the boost…
Hao Lin, Weiqi Luo, Kangkang Wei, Minglin Liu
—With the rapid development of deep learning technology, more and more face forgeries by deepfake are widely spread on social media, causing serious social concern. Face forgery detection has become a research hotspot in recent years, and many related methods have been proposed until now. For those images with low…
Joshua C.O. Koh, German Spangenberg, Surya Kant
Automated machine learning (AutoML) has been heralded as the next wave in artificial intelligence with its promise to deliver high performance end-to-end machine learning pipelines with minimal effort from the user. AutoML with neural architecture search which searches for the best neural network architectures in deep…
Atah Nuh Mih, Alireza Rahimi, Asfia Kawnine, Francis Palma + 3 more
in Resource-Constrained Edge Environment Authors: ['Atah Nuh Mih' 'Alireza Rahimi' 'Asfia Kawnine' 'Francis Palma' 'Mónica Wachowicz' 'Rickey Dubay' 'Hung Cao'] This paper proposes an optimization of an existing Deep Neural Network (DNN) that improves its hardware utilization and facilitates on-device training for…
Tam The Nguyen, Phong Minh Vu, Tung Thanh Nguyen
—In modern programming languages, exception handling is an effective mechanism to avoid unexpected runtime errors. Thus, failing to catch and handle exceptions could lead to serious issues like system crashing, resource leaking, or negative end-user experiences. However, writing correct exception handling code is often…
Authors not listed
As time-resolved x-ray absorption spectroscopy experiments become more prevalent, new tools are required to process and analyze the large amounts of data measured efficiently. To address this growing demand, we developed autoXAS: a python package for easy, fast, and reproducible processing and analysis of in-situ and…
Noah Trebesch, Emad Tajkhorshid
As more powerful high performance computing resources are becoming available, there is a new opportunity to bring the unique capabilities of molecular dynamics (MD) simulations to cell-scale systems. Membranes are ubiquitous within cells and are responsible for a diverse set of essential biological functions, but…