Maroof Ahmad

University of Kashmir

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D. K. Sadana

National Dairy Research Institute

D. S. Chahal

Bhagat Phool Singh Mahila Vishwavidyalaya

Safeer Alam

Ahsanullah University of Science and Technology

Butta Singh

Guru Nanak Dev University

A. K. Shrivastava

Jawaharlal Nehru Krishi Vishwa Vidyalaya

Harpal Singh

Lovely Professional University

Sandip K. Singh

Montana State University

Pushpendra Singh

Helmholtz-Zentrum Berlin für Materialien und Energie

L. B. Singh

Sardar Vallabhbhai Patel University of Agriculture & Technology

Mashooq Ahmad Dar

Polish Academy of Sciences

Cooperative Institutions

University of Kashmir

Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir

Veterinary & Animal Husbandry

Sher-i-Kashmir Institute of Medical Sciences

Govind Ballabh Pant University of Agriculture and Technology

Jamia Hamdard

Government Medical College

Krishi Vigyan Kendra, Ghatkhed Amravati

Daffodil International University

National Dairy Research Institute

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Factors affecting reproductive traits in Black Bengal and Beetal x Black Bengal crosses

Indian Journal of Small Ruminants (The) (2011)

Amit Kumar L. B. Singh Dhirendra Kumar Maroof Ahmad

The present study was undertaken on 351 records of Black Bengal and Beetal X Black Bengal does maintained at Goat Breeding Farm, Ranchi Veterinary College. The overall means were 388.88 days and 536.04 days for age at first conception and age at first kidding, respectively. Genetic group and birth weight had significant effect, while litter size at birth and season of birth had non-significant effect on these traits. Black Bengal goats had significantly lower age at first conception and age at first kidding.

BENGAL

Litter

Season of birth

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Citations (3)

Reproductive performance of Beetal goats in its breeding tract

Indian Journal of Small Ruminants (The) (2007)

Maroof Ahmad Palwinder Singh D. K. Sadana Safeer Alam D. S. Chahal

A study was undertaken on growth, reproductive performance, reproductive disorders and reproductive management of Beetal goats in its breeding tract. Data on 176 Beetal does belonging to 55 villages of 100 farmers of Gurdaspur District were studied. The average body weight at sexual maturity was found as 28.35 kg. The age at first conception, age at first kidding, kidding interval period, gestation length were observed to be 386.29, 522.83, 350.50 and 149.04 days, respectively. The kidding pattern in Beetal goats was found as 10.05, 77.76, 12.19 and 1.47 percent single, twin, triplet and quadruplet, respectively. The conception and kidding rate were observed to be 92.04 and 90.50 percent. The major reproductive disorders observed were abortion, retention of placenta and stillbirth.

Reproductive tract

Gestation period

Sexual maturity

Retained placenta

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Citations (8)

Deep Learning for Weak Supervision of Diabetic Retinopathy Abnormalities

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (2019)

Maroof Ahmad Nikhil Kasukurthi Harshit Pande

Deep learning-based grading of the fundus images of the retina is an active area of research. Various existing studies use different deep learning architectures on different datasets. Results of some of the studies could not be replicated in other studies. Thus a benchmarking study across multiple architectures spanning both classification and localization is needed. We present a comparative study of different state-of-the-art architectures trained on a proprietary dataset and tested on the publicly available Messidor-2 dataset. Although evidence is of utmost importance in AI-based medical diagnosis, most studies limit themselves to the classification performance and do not report the quantification of the performance of the abnormalities localization. To alleviate this, using class activation maps, we also report a comparison of localization scores for different architectures. For classification, we found that as the number of parameters increase, the models perform better, with NASNet yielding highest accuracy and average precision, recall, and F1-scores of around 95%. For localization, VGG19 outperformed all the models with a mean Intersection over Minimum of 0.45. We also found that there is a trade-off between classification performance and localization performance. As the models get deeper, their receptive field increases, causing them to perform well on classification but underperform on the localization of fine-grained abnormalities.

Benchmarking

Grading (engineering)

Contextual image classification

F1 score

Normalization

10.1109/isbi.2019.8759417

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Citations (24)

Productivity Change in Indian Manufacturing: A Comparison of Pre Reform and Post Reform Period

ANUSANDHAN – NDIM s Journal of Business and Management Research (2019)

Anubhuti Dwivedi Maroof Ahmad

The economic reforms were initiated in 1991 as part of the structural adjustment programme in India. It constituted of the three-pronged approach of Liberalization, Privatization and Globalization to boost investment, production and productivity in the economy. This paper attempts to analyse the trend of, technical efficiency, technological change and TFP growth in the Indian manufacturing sector during 1981-82 to 2011-12. The period up to 1990-91 is considered as pre-reform while the subsequent period is regarded as post-reform. The data used in this study for calculating productivity and its various components have been sourced from the Annual Survey of Industries (ASI) for the relevant years. The manufacturing sector is modelled as an industry producing a scalar output measured by the gross value added at constant prices by employing two-factor inputs namely labour and capital. Data Envelopment Analysis based Malmquist Index has been calculated to arrive at the estimates of technical efficiency, technological change and total factor productivity growth and a comparison has been made between pre-reform and post-reform period.

Malmquist index

Technical change

Investment

Economic reform

Gross output

Capital (architecture)

10.56411/anusandhan.2019.v1i2.46-51

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Citations (0)

Genetic estimates of growth and wool yield in Avikalin sheep

Indian Journal of Small Ruminants (The) (2004)

Maroof Ahmad C.V. Singh Rakesh Kumar Sharma Sushil Kumar A. L. Arora

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Citations (3)

Growth Performance and Survivability of Srinidhi birds under Farm System of Management

Journal of Krishi Vigyan (2019)

Maroof Ahmad Upasana Singh

Survivability

10.5958/2349-4433.2019.00023.0

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Citations (0)

Effect of feeding concentrate mixture and nutritional supplement in bucks with reduced libido and poor semen quality.

Indian Journal of Animal Production and Management (2009)

Dinesh Mahto Balraj Singh Maroof Ahmad

Semen quality

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Citations (2)

Comparison of different methods of heritability estimates for body weights and wool yield traits in avikalin crossbred sheep

Indian Journal of Small Ruminants (The) (2005)

Maroof Ahmad C.V. Singh Sushil Kumar A. L. Arora

Records of body weights and wool yield traits of 1313 lambs, the progeny of 106 sires and 134 baseline dams of Avikalin crossbred sheep were used to estimate the heritability and variance components. Traits analyzed were birth weight (BWT), weaning weight (WT-3), 6-month weight (WT-6), 12-month weight (WT-12) and first greasy fleece yield (GFY1). The estimate of habitability under model 2 and 8 of least squares analysis and univariate REML animal model were found to be 0.183, 0.170 and 0.168 for BWT, 0.259, 0.252 and 0.077 for WT-3, 0.365, 0.377 and 0.162 for WT-6, 0.445, 0.453 and 0.203 for WT-12 and 0.408, 0.412 and 0.107 for GFY1, respectively. Additive genetic variance was higher under model 2 of LSA than model 8 of LSA and univariate animal model. The univariate animal model estimated higher additive genetic variance than model 8 of LSA for all the five traits except BWT. Residual and phenotypic variances for all the three methods were almost similar and showed increasing trend with advancement of the age of animal.

Restricted maximum likelihood

Univariate

Animal model

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Citations (9)

Selection indices for improving commercial strain of White Leghorn

Indian Journal of Poultry Science (2001)

Maroof Ahmad Harpal Singh

Data recorded on 559 pullets progeny of 149 darns mated with 58 sires from single hatch of a commerical strain of White Leghorn, maintained by a poultry breeding organization were used in this investigation. The body weight at 12 and 36 weeks of age, age at sexual maturity, egg production upto 280 days of age and egg weight at 32 weeks of age, averaged as 820.06±3.75 g, 1616.97±6.78 g, 147.13±0.37 days, 108.56±0.52 eggs and 52.43±0.12 g, respectively. The heritablity estimates computed from sire component of variance of the above traits were 0.52±0.15, 0.59±0.16, 0.43±0.14. 0.38±0.13 and O.53±0.15 respectively. Sixteen multitrait selection indices constructed using the above five traits in different combinations were evaluated. On the basis of rIH (0.41) and ΔH (44.98 units) values, the index I1, comprising of all the five traits was found to be most efficient. The reduction in ΔH values due to noninclusion of different traits in the index revealed that 36 week body weight, 12 week body weight, egg production, egg weight and age at sexual maturity were relatively less important in the given order. Further it was observed that selection based on the Index comprising of body weightat 12 and 36 weeks of age and egg weight was almost as efficient as index I1.

Sire

Sexual maturity

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Citations (1)

Estimation of Sperm Concentration and Total Motility from Microscopic Videos of Human Semen Samples

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2018)

Karan Dewan Tathagato Rai Dastidar Maroof Ahmad

We present a method for automated analysis of human semen quality using microscopic video sequences of live semen samples. The videos are captured through an automated microscope at 400× magnification. In each video frame, objects of interest are extracted using image processing techniques. A deep convolution neural network (CNN) is used to distinguish between sperms and non-sperm objects. The frame-wise count of sperm cells is used to estimate the concentration of sperms in unit volume of semen. In each video, individual sperm cells are tracked across the frames using a predictive approach which handles collisions and occlusions well. Based on their computed trajectories, sperms are classified into progressively motile, nonprogressively motile and immotile types as per the WHO manual. In certain samples, due to various reasons, all visible objects drift in a certain direction. We present a method for identifying and compensating for the drift. Experimental results are presented on a set of more than 100 semen samples collected from a clinical laboratory. The results correlate well with existing accepted standard, SQA-V Gold for sperm concentration as well as motility parameters.

Frame rate

10.1109/cvprw.2018.00307

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Citations (14)