Institution
Islamia College University
Education•Peshawar, Pakistan•
About: Islamia College University is a education organization based out in Peshawar, Pakistan. It is known for research contribution in the topics: Density functional theory & Band gap. The organization has 645 authors who have published 1446 publications receiving 17074 citations. The organization is also known as: Islamia College Peshawar & ICU.
Topics: Density functional theory, Band gap, Electronic band structure, Dielectric, Optical conductivity
Papers published on a yearly basis
Papers
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TL;DR: This review article comprehensively discusses the background, concepts and future trends in phytoremediation of heavy metals.
2,718 citations
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TL;DR: A novel action recognition method by processing the video data using convolutional neural network (CNN) and deep bidirectional LSTM (DB-LSTM) network that is capable of learning long term sequences and can process lengthy videos by analyzing features for a certain time interval.
Abstract: Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great success in processing sequential multimedia data and yielded the state-of-the-art results in speech recognition, digital signal processing, video processing, and text data analysis. In this paper, we propose a novel action recognition method by processing the video data using convolutional neural network (CNN) and deep bidirectional LSTM (DB-LSTM) network. First, deep features are extracted from every sixth frame of the videos, which helps reduce the redundancy and complexity. Next, the sequential information among frame features is learnt using DB-LSTM network, where multiple layers are stacked together in both forward pass and backward pass of DB-LSTM to increase its depth. The proposed method is capable of learning long term sequences and can process lengthy videos by analyzing features for a certain time interval. Experimental results show significant improvements in action recognition using the proposed method on three benchmark data sets including UCF-101, YouTube 11 Actions, and HMDB51 compared with the state-of-the-art action recognition methods.
529 citations
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TL;DR: A novel convolutional neural network (CNN) based multi-grade brain tumor classification system that is experimentally evaluated on both augmented and original data and results show its convincing performance compared to existing methods.
471 citations
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TL;DR: A novel deep learning framework for the detection and classification of breast cancer in breast cytology images using the concept of transfer learning is proposed and it has been observed that the proposed framework outclass all the other deep learning architectures in terms of accuracy in detection and classified of breast tumor in cytological images.
471 citations
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TL;DR: This work has made an effort to summarize the isolated flavonoids with useful activities in order to gain a better understanding of their effects on human health.
Abstract: Flavonoids are phytochemical compounds present in many plants, fruits, vegetables, and leaves, with potential applications in medicinal chemistry. Flavonoids possess a number of medicinal benefits, including anticancer, antioxidant, anti-inflammatory, and antiviral properties. They also have neuroprotective and cardio-protective effects. These biological activities depend upon the type of flavonoid, its (possible) mode of action, and its bioavailability. These cost-effective medicinal components have significant biological activities, and their effectiveness has been proved for a variety of diseases. The most recent work is focused on their isolation, synthesis of their analogs, and their effects on human health using a variety of techniques and animal models. Thousands of flavonoids have been successfully isolated, and this number increases steadily. We have therefore made an effort to summarize the isolated flavonoids with useful activities in order to gain a better understanding of their effects on human health.
303 citations
Authors
Showing all 655 results
Name | H-index | Papers | Citations |
---|---|---|---|
Muhammad Tahir | 65 | 1636 | 23892 |
Javed Ali | 60 | 401 | 13573 |
Ghulam Murtaza | 53 | 1005 | 14516 |
Muhammad Sajid | 52 | 495 | 10089 |
Khan Muhammad | 45 | 186 | 6232 |
Iftikhar Ahmad | 41 | 515 | 7236 |
Abdur Rauf | 37 | 390 | 5432 |
Saeed Islam | 37 | 279 | 4415 |
Muhammad Imtiaz | 37 | 204 | 3983 |
Salman Khan | 34 | 118 | 3713 |
Habib Ahmad | 29 | 249 | 2850 |
Muhammad Ilyas | 29 | 253 | 4288 |
Muhammad Sajjad | 28 | 73 | 2346 |
Naeem Khan | 27 | 146 | 2709 |
Shafiullah Khan | 27 | 171 | 2336 |