Browsing by Author "Darshan, V."

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    Butterfly-Shaped Thiophene-Pyridine Hybrids: Green Electroluminescence and Large Third-Order Optical Nonlinearities
    (Wiley-VCH Verlag info@wiley-vch.de, 2020) Kakekochi, V.; Gangadharappa, S.C.; Nikhil, P.P.; Chandrasekharan, K.; Darshan, V.; Narayanan Unni, K.N.; Udayakumar, U.K.
    A set of four symmetric, butterfly-shaped 4-(4-(decyloxy)phenyl)-2,6-di(thiophen-2-yl)pyridine (TPY) derivatives 2TPA-TPY (TPY center and triphenylamine end groups), 2CBZ-TPY (TPY center and N-ethyl carbazole end groups), 2TPY-TPA (triphenylamine center and TPY at the periphery) and 2TPY-CBZ (N-ethyl carbazole center and TPY at the periphery) was synthesized. The molecules show reverse saturable absorption (RSA) which is consistent with two-photon absorption (2PA) associated with excited-state absorption (ESA) when excited using a 532 nm laser beam. The molecules 2TPA-TPY and 2TPY-TPA possess extremely low limiting thresholds of 1.73 and 2.68 J cm?2, respectively. An organic light-emitting diode (OLED) fabricated from 2TPA-TPY exhibits green emission with a maximum luminance of 207 cd m?2, a current efficiency (?CE) of 1.51cd A?1, a maximum power efficiency (?Pmax) of 0.46 lm W?1 and an external quantum efficiency (?EQE) of 0.48 % at 100 cd m?2. © 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim
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    Efficient Traffic Signboard Recognition System Using Convolutional Networks
    (Springer, 2020) Mothukuri, S.K.P.; Tejas, R.; Patil, S.; Darshan, V.; Koolagudi, S.G.
    In this paper, a smart automatic traffic sign recognition system is proposed. This signboard recognition system plays a vital role in the automated driving system of transport vehicles. The model is built based on convolutional neural network. The German Traffic Sign Detection Benchmark (GTSDB), a standard open-source segmented image dataset with forty-three different signboard classes is considered for experimentation. Implementation of the system is highly focused on processing speed and classification accuracy. These aspects are concentrated, such that the built model is suitable for real-time automated driving systems. Similar experiments are carried in comparison with the pre-trained convolution models. The performance of the proposed model is better in the aspects of fast responsive time. © Springer Nature Singapore Pte Ltd. 2020.