In this paper an efficient ISAR image classification method is proposed based on Minimum Enclosed Circle based Shape Matrix (MECSM) representation of the targets. Initially, discordant ISAR images are processed
2019; Cordeau and Laporte 2007) for a review on the optimization challenges, various algorithmic designs adopted over the years, a classification of existing ridesharing systems, models and algorithms for shared mobility, and finally models and solution methodologies for the dial-a-ride problem, ...
Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach Article Open access 17 January 2023 Lightweight convolutional neural network for chest X-ray images classification Article Open access 30 November 2024 Introduction...
The discriminator employs the Unet architecture, with the encoder performing classification by image and the decoder by pixel. This architectural improvement results in a stronger discriminator, which is encouraged to maintain a more powerful data representation, making it more difficult for the generator...
Hadjis, “Automatic Modulation Classification of Common Communication and Pulse Compression Radar Waveforms Using Cyclic Features,” master's thesis, Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio, USA, Mar. 2013, 96 pages. Heege et al., “Mapping of water depth, turbi...
In this paper, we proposed a new shape matrix representation mechanism for the automatic classification of targets from ISAR imagery. The proposed shape matrix representation method overcomes the undesirable side effects associated with the existing methods, such as the quantization of superfluous inner ...
Other questions were either dichotomous or classification questions. Results of the multiple-choice examinations from the obstetrics and gynecology course from the past 5 years were anonymously analyzed and compared with the current results. Examination questions were newly issued for each semester. ...
4. Considering the imbalance between negative and positive samples, we introduce weights to control negative and positive samples and the sample classification difficulty to obtain a novel confidence loss function, which can effectively improve the SAR ship target detection accuracy. The remainder of thi...