16 papers · ranked by Valyu relevance
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…
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…
Yixin Liu, Lihang Zhang, Zezhou Hao, Ziyuan Yang + 3 more
'Xiaoguang Zhou' 'Qing Chang'] To explore the application value of convolutional neural network combined with residual attention mechanism and Xception model for automatic classification of benign and malignant gastric ulcer lesions in common digestive endoscopy images under the condition of insufficient data. For the…
Ercument Yilmaz, Cansu Görürgöz, Hatice Cansu Kış, Emin Murat Canger + 1 more
'Bengi Öztaş'] Purpose This study aimed to develop an improved method for forensic age estimation using deep learning models applied to orthopantomography (OPG) images, focusing on distinguishing individuals under 12 years old from those aged 12 and above. Methods A dataset of 1941 pediatric patients aged between five…
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…
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…
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…
M. A. K. Hasan, Krishno Dey
The recent advancement of edge computing enables researchers to optimize various deep learning architectures to employ them in edge devices. In this study, we aim to optimize Xception architecture which is one of the most popular deep learning algorithms for computer vision applications. The Xception architecture is…
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…
B. M. Shahria Alam, Md. Nasim Ahmed
— Plant disease diagnosis is essential to farmers' management choices because plant diseases frequently lower crop yield and product quality. For harvests to flourish and agricultural productivity to boost, grape leaf disease detection is important. The plant disease dataset contains grape leaf diseases total of 9,032…
Zvi Baratz, Yaniv Assaf
Modeling individual traits is a long-standing goal of neuroscientific research, as it allows us to gain a more profound understanding of the relationship between brain structure and individual variability. In this article, we used the Keras-Tuner library to evaluate the performance of a tuned Xception convolutional…
Yukari Suzuki-Ohno, Thomas Westfechtel, Jun Yokoyama, Kazunori Ohno + 3 more
'Tohru Nakashizuka' 'Masakado Kawata' 'Takayuki Okatani'] Citizen science programs using organism photographs have become popular, but there are two problems related to photographs. One problem is the low quality of photographs. It is laborious to identify species in photographs taken outdoors because they are out of…
Lifeng Li, Zaimin Yang, Xiongping Yang, Jiaming Li + 1 more
With the increasing global demand for new energy sources, Photovoltaic (PV) is increasingly emphasized as a renewable energy source globally. Consequently, the assessment of PV resources has become crucial. Existing single frameworks and algorithms for PV resource assessment lead to low assessment accuracy. To…
Jamie Milne, Chen Qian, David Hargreaves, Yinhai Wang + 1 more
Using a relatively small training set of ∼16 thousand images from macromolecular crystallisation experiments, we compare classification results obtained with four of the most widely-used convolutional deep-learning network architectures that can be implemented without the need for extensive computational resources. We…