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Transformer-based and CNN-based models for clinically effective 2D and 3D pelvic bone segmentation in CT imaging. [PDF]

BMC Musculoskelet Disord
Nesheli SJ, Sabet M, Koozari A, Mirzaghavami P, Eftekhar A, Elhaie M, Rouhi S, Lariche NJ, Abidi M, Rezaeijo SM.   +9 more
europepmc   +1 more source

A federated multimodal deep learning framework for brain tumor classification using MRI. [PDF]

Front Artif Intell
Lakshmi Vasanthi K, Sree Darshne J, Venkatasubbu P, Ramasubramanian P.   +3 more
europepmc   +1 more source

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Detecting Affect States Using VGG16, ResNet50 and SE-ResNet50 Networks

SN Computer Science, 2020
Affect detection is a key component in developing intelligent human computer interface systems. State-of-the-art affect detection systems assume the availability of full un-occluded face images. This work uses convolutional neural networks with transfer learning to detect 7 basic affect states, viz. Angry, Contempt, Disgust, Fear, Happy and Sad.
Dhananjay Theckedath, R. R. Sedamkar
openaire   +1 more source

Verifikasi Kinship Dengan Arsitektur ResNet50

MDP Student Conference, 2023
Kinship adalah sistem kekerabatan antara dua orang atau lebih yang menunjukkan hubungan antara kedua orang tersebut dalam silsilah keluarga. Kinship secara biologi yang berkaitan dengan hubungan darah sehingga, fitur wajah yang dimiliki oleh seorang anak akan mengikuti fitur wajah dari orangtuanya.
Yohannes Yohannes, Beni Anthony
openaire   +1 more source

Cat classification based on improved ResNet50

Applied and Computational Engineering, 2023
Cat species recognition holds significant potential in many fields. The primary objective of this research is to develop an automated algorithm for recognizing the presence of cats in images. The application prospects of this algorithm are diverse and include security, image search, and social media.
openaire   +1 more source

An Improved YOLOv3 Model Based on ResNet50

2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI), 2020
In computer vision, object detection is one of the most challenging problems. In the one-stage object detection, YOLOv3 is one of the most popular object detection models. Because of its excellent detection speed and the same accuracy, it has a wide range of practical applications, and many kinds of derivative versions have been derived. In this paper,
Luoluo Huang, Guorong Chen, Jinchuan Huang, Bocheng Wang, Yixuan Zhang, Tingting Wen, Yao Liu, Hongli He   +7 more
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Road Garbage Classification Using ResNet50

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), 2023
Nomika Sree Kolla, Mythili Anumula, S Sujana, M Ratnababu   +3 more
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