India (National)
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Kamal Kant appears to heavily focus on local technology and consumer electronics, particularly smartphones. His coverage includes numerous press releases and private sector announcements related to smartphone launches, features, and comparisons.
Given Kamal's strong emphasis on smartphone launches and specifications, he may be receptive to pitches involving exclusive insights into upcoming smartphone models or detailed technical analysis of the latest devices from brands like Samsung, iPhone, OnePlus, Redmi, OPPO etc.
Kamal's coverage attributes suggest that he provides a platform for companies' product releases and updates. Therefore, PR professionals could consider offering him exclusive access to new products or in-depth data analyses regarding these tech gadgets.
It is important to note that Kamal focuses primarily on local (India) topics with a specific interest in Haryana and Gurgaon. This localized approach should be considered when crafting pitches for his attention.
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By: Mohammad Mahtab, Marwadi Universitly, King Khalid, Kamal Kant, Abdolali Yarahmadi, Taqi Mohammed Khattab
Within each iteration t, AdaBoost trains a weak classifier, denoted as h (x), to minimize the total weighted classification error over all training examples.
By: Shao Ren, Yueming, Sim, Shiwen, Ang, Kamal Kant, Zhu, Iong Ying, Yin, Yan Shan, Loh, Wang, Thorsten, Lipo, Sharma, Lin Yue Lanry, Yung
Yin and colleagues propose that diffraction-limited fluorescence videos contain hidden binding-type information. The authors present a deep learning model, T2C CNN, which exploits that hidden information to classify molecular interactions with high accuracy using a single dye in seconds.
By: Kamal Kant
Azusa Takeishi Yang Tian Kamal Kant Chandrakar Christina McCluskey Aaron Funk Courtney Schumacher
