A method for custom measurement of fish dimensions using the improved YOLOv5-keypoint framework with multi-attention mechanisms

Dimensional data directly reflects the growth rate of individual fish,an important economic trait of interest to fish researchers.Efficiently obtaining large-scale fish dimension data would be valuable for both selective breeding and production.To address this,our study proposes a custom dimension measurement method for fish using the YOLOv5-keypoint framework with multi-attention mechanisms.We optimized the YOLOv5 framework,incorporated the SimAM attention mechanism to achieve more accurate and faster fish detection,and added customizable landmarks to the network structure,enabling flexible configuration of the number and location of feature points in the training dataset.This method is applicable to various aquacultural species and other objects.We tested the effectiveness of the method using the economically important grass carp(Ctenopharyngodon idella).The proposed method outperforms pure YOLOv5,Faster R-CNN,and SSD in terms of precision and recall rates,achieving an impressive average precision of 0.9781.Notably,field trials confirmed the method's exceptional measurement accuracy,exceeding 97%compatibility with manual measurements,while demonstrating a realtime speed of 38 frames per second on the NVIDIA RTX A4000.This enables efficient and accurate large-scale surface dimension measurements of economic fish.To facilitate massive measurements in agricultural research,we have implemented this method as an online platform,called Mode-recognition Ruler(MrRuler,http://bioinf o.ihb.ac.cn/mrruler).The platform identifies objects in a single image at an average speed of 0.486±0.005 s,based on a dataset of 10,000 images.MrRuler includes two preset carp models and allows users to upload training datasets for custom models of their targets of interest.

DIMENSIONS OF MEASURE ON GENERAL SIERPINSKI CARPET

Let S = Pi(i=1)(infinity){0, 1, ..., r - 1} and (R) over bar the general Sierpinski carpet, Let mu be the induced probability measure on (R) over bar of <(mu)over tilde> on S by phi, where phi is the natural surjection from S onto (R) over bar and <(mu)over tilde> is the infinite product probability measure corresponding to probability vector (b(0), ..., b(r-1)) with b(i) = a(i)(logn) (m-1)/m(alpha). Authors show that dim(H) mu = (C) under bar(L)(mu) = (C) over bar(L)(mu) = (C) under bar(mu) = (C) over bar C(mu) = alpha.

ON THE EXACT HAUSDORFF MEASURE OF A CLASS OF SELF-SIMILAR SETS SATISFYING OPEN SET CONDITION

In this paper, we provide a new effective method for computing the exact value of Hausdorff measures of a class of self-similar sets satisfying the open set condition （OSC）. As applications, we discuss a self-similar Cantor set satisfying OSC and give a simple method for computing its exact Hausdorff measure.

Some Results on the Upper Convex Densities of the Self-Similar Sets at the Contracting-Similarity Fixed Points

In this paper, some results on the upper convex densities of self-similar sets at the contracting-similarity fixed points are discussed. Firstly, a characterization of the upper convex densities of self-similar sets at the contracting-similarity fixed points is given. Next, under the strong separation open set condition, the existence of the best shape for the upper convex densities of self-similar sets at the contracting-similarity fixed points is proven. As consequences, an open problem and a conjecture, which were posed by Zhou and Xu, are answered.

THE PACKING MEASURE OF A CLASS OF GENERALIZED SIERPINSKI CARPET

For 1/4< a <(?)/4, let S1(x) =ax, S2(x)=1-a+ax, x∈[0,1]. Ca is the attractor of the iteratedfunction system {S1,S2}, then the packing measure of Ca×Ca isPs(a)(Ca×Ca) = 4·2s(a)(1-a)s(a),where s(a) = -loga4.

NOTE ON THE PAPER “ AN NEGATIVE ANSWER TO A CONJECTURE ON THE SELF-SIMILAR SETS SATISFYING THE OPEN SET CONDITION”

In this paper, we present a more simple and much shorter proof for the main result in the paper ＂ An negative answer to a conjecture on the self-similar sets satisfy- ing the open set condition＂, which was published in the journal Analysis in Theory and Applications in 2009.

A NOTE ON MULTIFRACTAL PACKING DIMENSION OF MEASURES

The relations between the multifractal packing dimension of Borel probability measures and the asymptotic behavior of the function Ф＊（x）=limsup logv（B（x,r））-qlogu（B（x,r））/logr are discussed and some applications are given.

A study of making use of computer-aided projection fringe system to measure breast dimension

To measure breast basic dimension by using computer-aided projection fringe system.Methods A system has been developed for measuring breast basic dimension based on computer-aided projection fringe measurement and programming software.Plastic manikins breast’s SN-N (sternal notch to nipple distance),N-ML (nipple to midline distance),N-N (internipple distance),MBW (base width of breast) and N-IMF (nipple to inframammary fold distance) are measured with this system.At the same time,these items are also measured with routine ruler.Results This study indicate that the system has some merits:① non-touching measurement;② it is very rapid,the patient measured need hold his breath only 0.5 second,and all the time it takes is about 2.5 minutes;③ the measurement’s sensitivity is as high as to 0.6 mm,which meets the clinic requirement entirely;④ the measurement’s accuracy of the system is not significantly when comparing to the routine ruler’s.Conclusion Computer-adided projection fringe system for measuring breast basic dimension is feasible and advanced.14 refs,1 fig.

Hausdorff measure of sets of finite type of one-sided symbolic space

Some estimation formulae and a computation formula for the hausdorff meausre fo the sets of finite type of the one-sided symbolic space are given

A NOTE ON THE ASYMPTOTICS OF THE POLYMER MEASURES IN ONE DIMENSION

Given g∈(0,∞), we prove thatfor some constant C∈(0,∞), where (g, T) is the polymer measure defined on C_0([0, T]→R^1), and {W(t)}t∈[0,T] is the corresponding coordinate process.