Taoseef Ishtiak

913 total citations · 1 hit paper
7 papers, 454 citations indexed

About

Taoseef Ishtiak is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Taoseef Ishtiak has authored 7 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Networks and Communications, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in Taoseef Ishtiak's work include IoT and Edge/Fog Computing (1 paper), Automated Road and Building Extraction (1 paper) and Building Energy and Comfort Optimization (1 paper). Taoseef Ishtiak is often cited by papers focused on IoT and Edge/Fog Computing (1 paper), Automated Road and Building Extraction (1 paper) and Building Energy and Comfort Optimization (1 paper). Taoseef Ishtiak collaborates with scholars based in Bangladesh, Canada and Australia. Taoseef Ishtiak's co-authors include A. B. M. Shawkat Ali, Amir H. Gandomi, Nazifa Rafa, Mahtabin Rodela Rozbu, M. Mofijur, Shams Forruque Ahmed, Md. Sakib Bin Alam, Yuhong Guo, Sajid Ahmed and Md. Jakariya and has published in prestigious journals such as The Science of The Total Environment and Artificial Intelligence Review.

In The Last Decade

Taoseef Ishtiak

7 papers receiving 429 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning modelling techniques: current progress, applications, advantages, and challenges

2023 412 citations Shams Forruque Ahmed, Md. Sakib Bin Alam et al. Artificial Intelligence Review profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Taoseef Ishtiak Bangladesh	4	105	50	45	41	41	7	454
Susmita Ray India	5	178 1.7×	63 1.3×	32 0.7×	44 1.1×	68 1.7×	7	625
Yasser A. Ali Saudi Arabia	10	83 0.8×	57 1.1×	31 0.7×	27 0.7×	29 0.7×	26	428
Ravil I. Mukhamediev Kazakhstan	11	126 1.2×	71 1.4×	32 0.7×	63 1.5×	30 0.7×	35	468
Yan Kuchin Kazakhstan	10	125 1.2×	69 1.4×	31 0.7×	60 1.5×	23 0.6×	30	437
Адилхан Сымагулов Kazakhstan	8	97 0.9×	69 1.4×	30 0.7×	55 1.3×	24 0.6×	18	379
Manisha Sirsat Spain	8	127 1.2×	30 0.6×	127 2.8×	63 1.5×	41 1.0×	12	627
Mahady Hasan Bangladesh	11	75 0.7×	51 1.0×	85 1.9×	81 2.0×	59 1.4×	104	597
Yi Han China	8	116 1.1×	97 1.9×	35 0.8×	42 1.0×	109 2.7×	32	701
Yingchun Xia China	5	209 2.0×	42 0.8×	31 0.7×	24 0.6×	31 0.8×	12	493
Wenhao Lai China	11	96 0.9×	47 0.9×	29 0.6×	21 0.5×	72 1.8×	30	416

Countries citing papers authored by Taoseef Ishtiak

Since Specialization

Citations

This map shows the geographic impact of Taoseef Ishtiak's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Taoseef Ishtiak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taoseef Ishtiak more than expected).

Fields of papers citing papers by Taoseef Ishtiak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Taoseef Ishtiak. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Taoseef Ishtiak. The network helps show where Taoseef Ishtiak may publish in the future.

Co-authorship network of co-authors of Taoseef Ishtiak

This figure shows the co-authorship network connecting the top 25 collaborators of Taoseef Ishtiak. A scholar is included among the top collaborators of Taoseef Ishtiak based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Taoseef Ishtiak. Taoseef Ishtiak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Ahmed, Shams Forruque, Md. Sakib Bin Alam, Mahtabin Rodela Rozbu, et al.. (2023). Deep learning modelling techniques: current progress, applications, advantages, and challenges. Artificial Intelligence Review. 56(11). 13521–13617. 412 indexed citations breakdown →

2.

Ishtiak, Taoseef, et al.. (2023). Exemplar-FreeSOLO: Enhancing Unsupervised Instance Segmentation with Exemplars. 15424–15433. 4 indexed citations

3.

Ishtiak, Taoseef, et al.. (2020). Assessing climate-induced agricultural vulnerable coastal communities of Bangladesh using machine learning techniques. The Science of The Total Environment. 742. 140255–140255. 23 indexed citations

4.

Ishtiak, Taoseef, et al.. (2020). Comparative Study of Classifiers on Human Activity Recognition by Different Feature Engineering Techniques. 1. 93–101. 2 indexed citations

5.

Ishtiak, Taoseef, et al.. (2019). A Convolutional Neural Network Approach for Road Anomalies Detection in Bangladesh with Image Thresholding. 376–382. 3 indexed citations

6.

Ishtiak, Taoseef, et al.. (2019). A Minimalist Model of IoT based Sensor System for Sewage Treatment Plant Monitoring. 939–945. 9 indexed citations

7.

Ishtiak, Taoseef, et al.. (2017). An advanced application to decrease household power consumption and save energy detecting the weather condition. 2. 622–627. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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